| 0.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 2 | | adverbTags | | 0 | "she said quietly [quietly]" | | 1 | "she repeated flatly [flatly]" |
| | dialogueSentences | 15 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 0.333 | | effectiveRatio | 0.267 | |
| 88.53% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 436 | | totalAiIsmAdverbs | 1 | | found | | | highlights | | |
| 100.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 19.72% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 436 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "footsteps" | | 1 | "echoed" | | 2 | "eyebrow" | | 3 | "etched" | | 4 | "echoing" | | 5 | "gloom" |
| |
| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 1 | | maxInWindow | 1 | | found | | 0 | | label | "eyes widened/narrowed" | | count | 1 |
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| | highlights | | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 33 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 0 | | hedgeCount | 0 | | narrationSentences | 33 | | filterMatches | (empty) | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 42 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 25 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 435 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 6 | | unquotedAttributions | 0 | | matches | (empty) | |
| 15.27% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 21 | | wordCount | 334 | | uniqueNames | 5 | | maxNameDensity | 2.69 | | worstName | "Quinn" | | maxWindowNameDensity | 4.5 | | worstWindowName | "Eva" | | discoveredNames | | Harlow | 1 | | Quinn | 9 | | Tube | 1 | | Kowalski | 1 | | Eva | 9 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Kowalski" | | 3 | "Eva" |
| | places | (empty) | | globalScore | 0.153 | | windowScore | 0.167 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 25 | | glossingSentenceCount | 0 | | matches | (empty) | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 435 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 42 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 15 | | mean | 29 | | std | 16.25 | | cv | 0.56 | | sampleLengths | | 0 | 68 | | 1 | 46 | | 2 | 46 | | 3 | 13 | | 4 | 15 | | 5 | 17 | | 6 | 40 | | 7 | 18 | | 8 | 12 | | 9 | 38 | | 10 | 7 | | 11 | 25 | | 12 | 35 | | 13 | 20 | | 14 | 35 |
| |
| 94.63% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 1 | | totalSentences | 33 | | matches | | |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 0 | | totalVerbs | 66 | | matches | (empty) | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 42 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 334 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 7 | | adverbRatio | 0.020958083832335328 | | lyAdverbCount | 6 | | lyAdverbRatio | 0.017964071856287425 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 42 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 42 | | mean | 10.36 | | std | 4.82 | | cv | 0.466 | | sampleLengths | | 0 | 18 | | 1 | 11 | | 2 | 25 | | 3 | 14 | | 4 | 12 | | 5 | 10 | | 6 | 15 | | 7 | 9 | | 8 | 14 | | 9 | 12 | | 10 | 20 | | 11 | 6 | | 12 | 7 | | 13 | 4 | | 14 | 11 | | 15 | 8 | | 16 | 9 | | 17 | 16 | | 18 | 6 | | 19 | 7 | | 20 | 11 | | 21 | 7 | | 22 | 6 | | 23 | 5 | | 24 | 8 | | 25 | 4 | | 26 | 16 | | 27 | 10 | | 28 | 7 | | 29 | 5 | | 30 | 3 | | 31 | 4 | | 32 | 6 | | 33 | 19 | | 34 | 11 | | 35 | 11 | | 36 | 13 | | 37 | 14 | | 38 | 6 | | 39 | 12 | | 40 | 10 | | 41 | 13 |
| |
| 74.60% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.47619047619047616 | | totalSentences | 42 | | uniqueOpeners | 20 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 31 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 9 | | totalSentences | 31 | | matches | | 0 | "Her footsteps echoed off the" | | 1 | "She emerged onto a forgotten" | | 2 | "She clutched a worn leather" | | 3 | "She glanced up as Quinn" | | 4 | "She crouched down, examining the" | | 5 | "she said quietly" | | 6 | "she repeated flatly" | | 7 | "she said, her voice low" | | 8 | "She strode off down the" |
| | ratio | 0.29 | |
| 8.39% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 28 | | totalSentences | 31 | | matches | | 0 | "Detective Harlow Quinn ducked under" | | 1 | "The air hung heavy with" | | 2 | "Her footsteps echoed off the" | | 3 | "She emerged onto a forgotten" | | 4 | "Quinn's sharp gaze swept the" | | 5 | "Eva Kowalski stood off to" | | 6 | "She clutched a worn leather" | | 7 | "She glanced up as Quinn" | | 8 | "Eva said, her voice tight" | | 9 | "Quinn cocked an eyebrow." | | 10 | "Eva hesitated, her eyes darting" | | 11 | "Quinn followed her gaze, taking" | | 12 | "She crouched down, examining the" | | 13 | "Eva shifted nervously, hugging her" | | 14 | "she said quietly" | | 15 | "Quinn stood, fixing Eva with" | | 16 | "Eva bit her lip, then" | | 17 | "The casing was etched with" | | 18 | "Quinn's eyes narrowed." | | 19 | "she repeated flatly" |
| | ratio | 0.903 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 31 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 19 | | technicalSentenceCount | 0 | | matches | (empty) | |
| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 2 | | matches | | 0 | "Eva said, her voice tight" | | 1 | "she said, her voice low" |
| |
| 16.67% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 6 | | fancyCount | 2 | | fancyTags | | 0 | "she muttered (mutter)" | | 1 | "she repeated flatly (repeat)" |
| | dialogueSentences | 15 | | tagDensity | 0.4 | | leniency | 0.8 | | rawRatio | 0.333 | | effectiveRatio | 0.267 | |